A mathematical model of the thermal processing of cylindrical meat emulsion products has been developed and solved numerically using the finite difference method. The model was used to predict the cooking time and moisture loss in continuously or batch operated processing equipment. Thermal schedules with changing processing conditions and a stochastic variation of process parameters could be simulated. The mathematical model was explored as a tool for designing optimal processing protocols for meat emulsions with different heat and mass transfer properties. The values of the concentration dependent effective moisture diffusion coefficient, the equilibrium moisture content and the overall heat transfer coefficient were found to exhibit a strong influence on the results of the simulation. A pulsed field gradient spin-echo nuclear magnetic resonance method (PFGNMR) was used to measure the moisture self diffusion coefficient of the meat emulsion. Because of the strongly different time scales of the PFGNMR experiments and actual thermal meat emulsion processing, difficulties exist in relating the obtained values to the effective moisture diffusion coefficient during processing. It is proposed to directly obtain moisture profiles for emulsion products removed at the different times from the processing environment by means of Magnetic Resonance Imaging. This data would allow to test the assumptions made in the mathematical model and to extract key parameters by using a multi response nonlinear regression software package.